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from enthought.enable.api import Pointer
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from enthought.enable.tools.drag_tool import DragTool
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from enthought.traits.api import Bool, Enum, Float, Tuple
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class PanTool(DragTool):
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""" An implementation of a pan tool based on the DragTool instead of
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# The cursor to use when panning.
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drag_pointer = Pointer("hand")
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# Scaling factor on the panning "speed".
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# The modifier key that, if depressed when the drag is initiated, constrains
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# the panning to happen in the only direction of largest initial motion.
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# It is possible to permanently restrict this tool to always drag along one
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# direction. To do so, set constrain=True, constrain_key=None, and
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# constrain_direction to the desired direction.
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constrain_key = Enum(None, "shift", "control", "alt")
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# Constrain the panning to one direction?
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constrain = Bool(False)
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# The direction of constrained draw. A value of None means that the user
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# has initiated the drag and pressed the constrain_key, but hasn't moved
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# the mouse yet; the magnitude of the components of the next mouse_move
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# event will determine the constrain_direction.
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constrain_direction = Enum(None, "x", "y")
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# Restrict to the bounds of the plot data
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restrict_to_data = Bool(False)
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# (x,y) of the point where the mouse button was pressed.
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# Data coordinates of **_original_xy**. This may be either (index,value)
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# or (value,index) depending on the component's orientation.
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_original_data = Tuple
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# Was constrain=True triggered by the **contrain_key**? If False, it was
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# set programmatically.
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_auto_constrain = Bool(False)
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#------------------------------------------------------------------------
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# Inherited BaseTool traits
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#------------------------------------------------------------------------
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# The tool does not have a visual representation (overrides
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# The tool is not visible (overrides BaseTool).
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# The possible event states of this tool (overrides enable.Interactor).
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#event_state = Enum("normal", "panning")
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def drag_start(self, event):
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""" Called when the drag operation starts """
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self._start_pan(event)
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def dragging(self, event):
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if self._auto_constrain and self.constrain_direction is None:
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# Determine the constraint direction
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if abs(event.x - self._original_xy[0]) > abs(event.y - self._original_xy[1]):
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self.constrain_direction = "x"
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self.constrain_direction = "y"
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for direction, bound_name, ndx in [("x","width",0), ("y","height",1)]:
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if not self.constrain or self.constrain_direction == direction:
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mapper = getattr(plot, direction + "_mapper")
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domain_min, domain_max = mapper.domain_limits
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eventpos = getattr(event, direction)
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origpos = self._original_xy[ndx]
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screenlow, screenhigh = mapper.screen_bounds
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screendelta = self.speed * (eventpos - origpos)
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#if getattr(plot, direction + "_direction", None) == "flipped":
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# screendelta = -screendelta
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newlow = mapper.map_data(screenlow - screendelta)
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newhigh = mapper.map_data(screenhigh - screendelta)
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# Don't set the range in this dimension if the panning
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# would exceed the domain limits.
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# To do this offset properly, we would need to iteratively
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# solve for a root using map_data on successive trial
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# values. As a first approximation, we're just going to
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# use a linear approximation, which works perfectly for
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# linear mappers (which is used 99% of the time).
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if domain_min is None:
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if self.restrict_to_data:
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domain_min = min([source.get_data().min() for source in range.sources])
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if domain_max is None:
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if self.restrict_to_data:
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domain_max = max([source.get_data().max() for source in range.sources])
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if (newlow <= domain_min) and (newhigh >= domain_max):
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# Don't do anything; effectively, freeze the pan
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if newlow <= domain_min:
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delta = newhigh - newlow
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# Don't let the adjusted newhigh exceed domain_max; this
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# can happen with a nonlinear mapper.
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newhigh = min(domain_max, domain_min + delta)
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elif newhigh >= domain_max:
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delta = newhigh - newlow
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# Don't let the adjusted newlow go below domain_min; this
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# can happen with a nonlinear mapper.
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newlow = max(domain_min, domain_max - delta)
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# Use .set_bounds() so that we don't generate two range_changed
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# events on the DataRange
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range.set_bounds(newlow, newhigh)
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self._original_xy = (event.x, event.y)
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plot.request_redraw()
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def drag_cancel(self, event):
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# We don't do anything for "cancelling" of the drag event because its
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# transient states during the drag are generally valid and useful
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# terminal states unto themselves.
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def drag_end(self, event):
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return self._end_pan(event)
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def _start_pan(self, event, capture_mouse=True):
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self._original_xy = (event.x, event.y)
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if self.constrain_key is not None:
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if getattr(event, self.constrain_key + "_down"):
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self.constrain = True
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self._auto_constrain = True
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self.constrain_direction = None
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self.event_state = "panning"
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event.window.set_pointer(self.drag_pointer)
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event.window.set_mouse_owner(self, event.net_transform())
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def _end_pan(self, event):
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if self._auto_constrain:
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self.constrain = False
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self.constrain_direction = None
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self.event_state = "normal"
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event.window.set_pointer("arrow")
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if event.window.mouse_owner == self:
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event.window.set_mouse_owner(None)
added
removed
enthought/chaco/tools/pan_tool2.py
